How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Finite-range lattice DLR existence and closed convex state set
Statement
Assume Countable Choice, a finite nonempty alphabet , and a proper consistent finite-range specification on , with finite range as defined in Lattice Gibbs kernels and DLR states. No translation invariance is required. For every exhaustion and every sequence of exterior configurations , the measures extended with the fixed exterior have a cylinder-convergent subsequence. Every such subsequential limit is a DLR state. Consequently the DLR state set is nonempty, convex, and closed under cylinder convergence. No uniqueness is asserted.
Facts & Assumptions
Given: A proper consistent finite-range lattice specification, an exhausting sequence of finite volumes, exterior configurations, and Countable Choice for the product-measure extension.
Assume Countable Choice: every countable family of nonempty sets has a choice function (The Axiom of Countable Choice ()). The measure-extension and probability-compactness conclusions used below are supplied by [F1], not by this axiom definition.
The specification is proper, consistent, and finite range in the cylinder-local sense of Lattice Gibbs kernels and DLR states.
Cylinder convergence is sequentially compact and determines a unique probability measure under Countable Choice (Finite-alphabet product and probability compactness).
Proof
Each proper kernel value is already a probability measure on . By [F1], a subsequence converges on every cylinder to a probability measure .
Fix a finite and cylinder event . By [A2], choose a finite coordinate set on which depends. For sufficiently large , . Consistency in [A2] then gives , and both integrands are cylinder functions, so cylinder convergence passes the identity to .
Cylinder events form a pi-system generating the Borel sigma-algebra. The two probability measures and agree on the generating cylinders by step 2.1. Uniqueness of measures on the cylinder-generated sigma-algebra, part of [F1], extends equality to every Borel event. Thus is DLR for each .
Convex combinations preserve the linear identities . A cylinder-convergent limit of DLR laws satisfies the same local identities by the argument of step 2.1, hence is DLR. Since step 1.1 constructs at least one such law, the state set is nonempty, convex and closed.
Remarks
The cited Princeton notes make different broad claims about projective consistency in distinct model sections: the O existence discussion at PDF pp. 16–17 says its finite-volume Gibbs laws do not satisfy the Kolmogorov-extension consistency hypothesis, while the Ising/DLR discussion at pp. 31–32 says the finite-volume family is consistent in that sense. Because those passages concern different model sections, they do not by themselves establish a contradiction for the finite-alphabet specification in this theorem. Neither passage is used here. This proof obtains a DLR state from a cylinder-convergent subsequence, local kernel consistency, and measure extension; it does not treat the finite-volume laws as a projectively consistent family.